Corina Carpentier AquaLife Workshop, Kiel, Germany 2nd June 2010

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Presentation transcript:

Corina Carpentier AquaLife Workshop, Kiel, Germany 2nd June 2010 Sources of variability in phytobenthos biomass measurements using the BenthoFluor Corina Carpentier AquaLife Workshop, Kiel, Germany 2nd June 2010

Introduction Why phytobenthos analysis in rivers? Why in situ phytobenthos measurements? Sources of variability substrate patchy distribution representativeness of results

European Water Framework Directive (WFD) Impact Ecological Status { None or minimal HIGH GOOD MODERATE POOR BAD No deterioration Low { Restoration Moderate { High { Severe { Links between chemical and ecological status? Courtesy Peter Pollard, Scottish Environment Protection Agency

Implementation of the WFD biological quality elements hydro-morphological pressures nutrients organic pollution toxicity acidification benthic invertebrates ++ +++ + phytobenthos, macrophytes - phytoplankton fish

Research objective Development of a method for the assessment of phytobenthos biomass as an indicator for the trophic status of flowing waters This method has to be: sufficiently sensitive for trophic status assessment practical fast cheap

CEN Guidance Standards EN 13946 and 14407: removal efficiency of sampling procedure? Substrate Before (µg/cm2) After (µg/cm2) removal cyanobacteria 1.20 0.45 62.4% diatoms 0.17 0.15 13.4%

Avoid sampling errors by performing in situ measurements BenthoFluor measurements in the field: many measurements in a short time determine suitable spots for biodiversity sampling major difference as compared to phytoplankton analysis: the presence of a substrate

The influence of the substrate black plastic Black cloth dye-filter 10.5 µg/cm2 12.8 µg/cm2

Substrate-dependent correction factor

Reflection factor based on 700 nm value yi = bixi (1+baixi) yi = real value at wavelength i; xi = raw value at wavelength i; ai = wavelength-dependent empirical factor; b = factor expressing the reflection properties of the substrate (b = 1 for stone; b = 2.1 for black background) substrate original result (µg/cm2) black (µg/cm2) stone corrected result (µg/cm2) 700nm black 10.47 stone 7 p1 19.29 (+84%) 7.38 (-29%) 9.90 (-5.5%) stone 7 p2 17.10 (+63%) 6.61 (-37%) 10.02 (-4.3%) stone 8 p3 11.89 (+ 13.5%) 4.78 (-54%) 11.28 (+7.7%) stone 8 p4 11.23 (+ 7.3%) 4.57 (-56%) 10.96 (+4.7%)

Patchy distribution Hildebrandia rivularis

Patchiness (2) sample green algae (µg/cm2) cyanobacteria (µg/cm2) diatoms (µg/cm2) 1 0.00 1.58 0.34 2 0.55 1.01 3 1.12 0.72 4 0.26 1.00 0.44

CEN Guidance Standards EN 13946 and 14407: 5 samples per site left bank right bank Danube River, Bratislava (SK)

How many measurements? 1.46 0.41 0.26

Danube River data: 2,477 measurements Width of 95% CI: 0.5  reached after 33 measurements n = 33

In conclusion Substrate-dependent correction factor improves results considerably In situ BenthoFluor measurements provide insight into patchy distribution of phytobenthos Limited number of measurements (25-35) provides statistically representative results in little time (appr. 10-15 minutes)

Thank you for your attention! Corina Carpentier AquaLife Workshop, Kiel, Germany 2nd June 2010